Volahi DEEP LEARNING MANAGEMENT PLATFORM
Machine Orchestration, Version Control and Pipeline Management for Deep Learning
THE DEEP LEARNING PLATFORM FOR DATA SCIENTISTS
TRACK EVERYTHING
We believe that effective version control is the only way to achieve reproducibility, regulatory compliance, an audit trail & quick results.
Whether from today, or 10 years from now, you’ll be able to select a deployed model and clearly trace back through its hyperparameters, training data, script version, associated cost, sibling models & even the team members involved in training it.
VISUALIZE AND MONITOR
You’ll see everything in real-time as your trainings progress, no longer stuck manually launching models and keeping track of CSV files. Get visual feedback on everything from a single model’s performance to a convergence of several parallel hyperparameter sweeps. See how your parameter sweeps are progressing while comparing competing models by accuracy, depth, or any custom parameter. You can also output custom parameters into stdout and see it graphically in the Valohai web interface.
INTEGRATE EVERYWHERE
Valohai works with any runtime you have and runs any machine learning code you write. Unlike other deep learning tools, we don’t tie you down to one vendor (not even to ourselves – even the configuration format is open source).
Run your TensorFlow, Keras, CNTK, Caffe, Darknet, DL4J, PyTorch, MXNet, or anything from bash scripts to C-code in your Docker wrapper of choice. Store your training data and labels in an Azure Blob, AWS S3 bucket, or your own FTP server. Access your code in any public or private Git repository and run it on your cloud or on-premises hardware of choice.
STANDARDIZED WORKFLOW
Valohai puts the same tools and industry-leading best practises at your fingertips used by powerhouses like Uber, Netflix, AirBnB and Facebook for managing their internal machine learning pipelines.
Valohai’s streamlined machine learning pipeline ensures that steps integrate together, regardless of who wrote the code or which language or framework was used. Generate images with Unity, transform in custom C-code, train with TensorFlow in Python, Deploy to a Kubernetes cluster. Everything works out of the box!
AUTOMATE COMPLEX DATA PIPELINES
Everything in Valohai is built API-first for easy integration of your ML pipeline into your existing software pipeline, e.g. through Jenkins or any other continuous integration platform.
POWERFUL MACHINE ORCHESTRATION
LIMITLESS PERFORMANCE
Valohai lets you scale up vertically and horizontally to do distributed learning and parallel hyperparameter sweeps at the speed of light (in an ethernet cable). Run your model in parallel on a hundred GPUs or tell Valohai to sweep through different hyperparameters to find the best model for your data in parallel on dozens of TPUs. Valohai is built for finding and optimizing your model for big data and immense models that scale with you, as you grow from data exploration to production.
ZERO-SETUP INFRASTRUCTURE
Train your models in the cloud or on your own server-farm with the click of a button, the call of an API, or a CLI one-liner. Valohai enables you to use the right amount of processing units - maximizing your results while saving time & money.
SCALE FAST AND WITHOUT EFFORT
Valohai supports massive-scale concurrency on top of AWS, Microsoft Azure, Google Cloud Platform & on-premises hardware (e.g. OpenStack). Just click a button and launch your code within Dockers containers on your hardware of choice.
AUTOMATE YOUR VERSION CONTROL
Fulfill regulatory compliance without added work. Valohai automatically tracks all your experiments, with a clear picture of how each model was trained, from data to parameters & statistics to algorithm. Rerun previous experiments anytime.
PIPELINE MANAGEMENT
Don’t worry about environments, configurations or shutting down servers when your training is done. Streamlined and expandable Valohai API allows you to concentrate on trials & mastering your models!
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